MOD 20776: Engineering Data with Microsoft Cloud Services

Description

Duration: 5 days

During this five-day instructor-led course, students will learn how to process Big Data using Azure tools and services including Azure Stream Analytics, Azure Data Lake, Azure SQL Data Warehouse, and Azure Data Factory. ow to include custom functions, and integrate Python and R Is also covered in this course.

Data engineers, IT professionals, developers, and information workers; who plan to implement big data engineering workflows on Azure are the focused individuals for this course.

Upon completion of this course, students will be able to:

Describe common architectures for processing big data using Azure tools and services
Describe how to use Azure Stream Analytics to design and implement stream processing over large-scale data
Describe how to include custom functions and incorporate machine learning activities into an Azure Stream Analytics job
Describe how to use Azure Data Lake Store as a large-scale repository of data files
Describe how to use Azure Data Lake Analytics to examine and process data held in Azure Data Lake Store
Describe how to create and deploy custom functions and operations, integrate with Python and R, and protect and optimize jobs
Describe how to use Azure SQL Data Warehouse to create a repository that can support large-scale analytical processing over data at rest
Describe how to use Azure SQL Data Warehouse to perform analytical processing, how to maintain performance, and how to protect the data
Describe how to use Azure Data Factory to import, transform, and transfer data between repositories and services
Describe the purpose of Azure Data Factory, and explain how it works
Describe how to create Azure Data Factory pipelines that can transfer data efficiently
Describe how to perform transformations using an Azure Data Factory pipeline
Describe how to monitor Azure Data Factory pipelines, and how to protect the data flowing through these pipelines

Prerequisites

In addition to their professional experience, it is recommended that students attending this course have:

A good understanding of Azure data services
Basic knowledge of the Microsoft Windows operating system and its core functionality
Good knowledge of relational databases

What’s included?

  • Authorized Courseware
  • Intensive Hands on Skills Development with an Experienced Subject Matter Expert
  • Hands-on practice on real Servers and extended lab support 1.800.482.3172
  • Examination Vouchers & Onsite Certification Testing- (excluding Adobe and PMP Boot Camps)
  • Academy Code of Honor: Test Pass Guarantee
  • Optional: Package for Hotel Accommodations, Lunch and Transportation

With several convenient training delivery methods offered, The Academy makes getting the training you need easy. Whether you prefer to learn in a classroom or an online live learning virtual environment, training videos hosted online, and private group classes hosted at your site. We offer expert instruction to individuals, government agencies, non-profits, and corporations. Our live classes, on-sites, and online training videos all feature certified instructors who teach a detailed curriculum and share their expertise and insights with trainees. No matter how you prefer to receive the training, you can count on The Academy for an engaging and effective learning experience.

Methods

  • Instructor Led (the best training format we offer)
  • Live Online Classroom – Online Instructor Led
  • Self-Paced Video

Speak to an Admissions Representative for complete details

StartFinishPublic PricePublic Enroll Private PricePrivate Enroll
12/25/202312/29/2023
1/15/20241/19/2024
2/5/20242/9/2024
2/26/20243/1/2024
3/18/20243/22/2024
4/8/20244/12/2024
4/29/20245/3/2024
5/20/20245/24/2024
6/10/20246/14/2024
7/1/20247/5/2024
7/22/20247/26/2024
8/12/20248/16/2024
9/2/20249/6/2024
9/23/20249/27/2024
10/14/202410/18/2024
11/4/202411/8/2024
11/25/202411/29/2024
12/16/202412/20/2024
1/6/20251/10/2025

Curriculum

Module 1: Architectures for Big Data Engineering with Azure
Lessons

Understanding Big Data
Architectures for Processing Big Data
Considerations for designing Big Data solutions
Lab: Designing a Big Data Architecture

Design a big data architecture

Module 2: Processing Event Streams using Azure Stream Analytics
Lessons

Introduction to Azure Stream Analytics
Configuring Azure Stream Analytics jobs
Lab: Processing Event Streams with Azure Stream Analytics

Create an Azure Stream Analytics job
Create another Azure Stream job
Add an Input
Edit the ASA job
Determine the nearest Patrol Car

Module 3: Performing custom processing in Azure Stream Analytics
Lessons

Implementing Custom Functions
Incorporating Machine Learning into an Azure Stream Analytics Job
Lab: Performing Custom Processing with Azure Stream Analytics

Add logic to the analytics
Detect consistent anomalies
Determine consistencies using machine learning and ASA

Module 4: Managing Big Data in Azure Data Lake Store
Lessons

Using Azure Data Lake Store
Monitoring and protecting data in Azure Data Lake Store
Lab: Managing Big Data in Azure Data Lake Store

Update the ASA Job
Upload details to ADLS

Module 5: Processing Big Data using Azure Data Lake Analytics
Lessons

Introduction to Azure Data Lake Analytics
Analyzing Data with U-SQL
Sorting, grouping, and joining data
Lab: Processing Big Data using Azure Data Lake Analytics

Add functionality
Query against Database
Calculate average speed

Module 6: Implementing custom operations and monitoring performance in Azure Data Lake Analytics
Lessons

Incorporating custom functionality into Analytics jobs
Managing and Optimizing jobs
Lab: Implementing custom operations and monitoring performance in Azure Data Lake Analytics

Custom extractor
Custom processor
Integration with R/Python
Monitor and optimize a job

Module 7: Implementing Azure SQL Data Warehouse
Lessons

Introduction to Azure SQL Data Warehouse
Designing tables for efficient queries
Importing Data into Azure SQL Data Warehouse
Lab: Implementing Azure SQL Data Warehouse

Create a new data warehouse
Design and create tables and indexes
Import data into the warehouse.

Module 8: Performing Analytics with Azure SQL Data Warehouse
Lessons

Querying Data in Azure SQL Data Warehouse
Maintaining Performance
Protecting Data in Azure SQL Data Warehouse
Lab: Performing Analytics with Azure SQL Data Warehouse

Performing queries and tuning performance
Integrating with Power BI and Azure Machine Learning
Configuring security and analyzing threats

Module 9: Automating the Data Flow with Azure Data Factory
Lessons

Introduction to Azure Data Factory
Transferring Data
Transforming Data
Monitoring Performance and Protecting Data
Lab: Automating the Data Flow with Azure Data Factory

Automate the Data Flow with Azure Data Factory